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Show HN: Shoehorn – Quantize any model down to run on your machine

Working on Mac, Linux, and Windows now. I include a simple GUI to find new models and get things built and set up. It is working quite well across a few models for me. The GitHub README and DESIGN.md files go into detail of the how/why and it's working remarkably well so far. https://github.com/notactuallytreyanastasio/shoehorn

66 points by rhgraysonii - 17 comments

17 Comments

puttycat [3 hidden]5 mins ago
This is really impressive. Can you say a bit about the underlying process? I'm guessing this is post-training qantization? Isn't PTQ also resource-intensive? (Ie might not work on any machine)
sscarduzio [3 hidden]5 mins ago
The project name is perfect!
hmokiguess [3 hidden]5 mins ago
Reminds me of https://github.com/AlexsJones/llmfit
rhgraysonii [3 hidden]5 mins ago
LLMFit tells you what can run on something. I built something quite similar to their search into Shoehorn now.
jedbrooke [3 hidden]5 mins ago
I gotta laugh at some of the models it suggests, for example:

> AnkitAI/Parable-Qwen3-4B-Claude-Fable-5-GGUF

you’re telling me you managed to fit Fable 5 into just 4B?

chompychop [3 hidden]5 mins ago
I gotta laugh at your thought process: knowing Fable 5 is a large frontier model, you're telling me that the first thing that came to your mind on seeing that model name is that it's a quantized version of Fable? As opposed to a distillation/fine-tuning on Fable responses?
metalliqaz [3 hidden]5 mins ago
Well to be fair here... the title of this post doesn't mention fine tuning, it mentions quantization.
unrented7977 [3 hidden]5 mins ago
Don't make fun of people you think are ignorant, it's a pretty shitty look
chompychop [3 hidden]5 mins ago
Well, then don't get all snarky and dismissive of things you might not be knowledgeable about ("you" here referring to OP).
akshay_akula [3 hidden]5 mins ago
This is interesting. I wonder how it could work with something like https://github.com/JustVugg/colibri.
mbuchel-hn [3 hidden]5 mins ago
does this work similar to airllm? i am wondering how it would handle something like quantizing kimi k3 on a budget of 8 gbs, or is that something you are not attempting to solve yet?
rhgraysonii [3 hidden]5 mins ago
Yes that is exactly what this does.
kennywinker [3 hidden]5 mins ago
Could you explain what happens when you try to shoehorn a 2.4T parameter model into a 24gb m4 mac?
metalliqaz [3 hidden]5 mins ago
extreme divergence would be my guess
akshay_akula [3 hidden]5 mins ago
Wondering the same thing but for 48gb M5 Max.
jaylane [3 hidden]5 mins ago
tried it out but based on the model sizing result i got i got an insufficient memory error when the server started running
rhgraysonii [3 hidden]5 mins ago
If you could post an issue if you still have the error around that would be awesome.